EAISI Research Track

How to trust AI?

In the Summit research track, TU/e researchers and partners will present their latest findings, specifically around this theme. In the midst of AI developments that lead to doubts or even fear, we put some necessary focus on the positive influence AI has and will have on our lives and the real world around us. Please join the discussions and get to know in detail what is happening in the center of Brainport’s AI research.

Timetable EAISI Research Track

11:00 Coffee break and Expo  
11:30 Dominique Fürst Welcome
11:35 Alessandro Saccon Robotics manipulation in the open world: challenges and opportunities 
12:00 Mauro Salazar Autonomous Vehicles, Safety Halo, Mobility Systems, Wellbeing
12:25 Valentina Breschi To collaborate or to compete, is that the question to achieve explainability? 
12:35 Meike Nauta & Nienke Bakx  Beyond Explainability: Building Trust through Interactive, Interpretable AI
13:00 Lunch break & Expo  
14:15 Dominique Fürst Opening afternoon track
14:20 Mathias Funk & Jon Pluyter AI has trust issues, a therapy session
14:45 Isel Garcia Grau SOFI: A Sparseness-Optimized Feature Importance method
15:10 Guang Hu Trusting AI for Sustainable Energy Integration
15:18 Giulia de Pasquale Mitigating Biases in Decision-Making Systems
15:25 Barend de Rooij Trust as a Techno-epistemic Virtue
15:50 Bert de Vries & Albert Podusenko  How to Trust AI: Embracing Uncertainty with Probabilistic Methods
16:15 Carlo van de Weijer Central Closing

 

 

Image

At EAISI 1000+ AI-researchers do research on AI systems where the physical, digital, and human worlds come together. EAISI aims to get to a better understanding, better designs, better models, and better decisions in the application areas of Health, Mobility, and High-Tech Systems.

EAISI Research Track

How to trust AI?

In the Summit research track, TU/e researchers and partners will present their latest findings, specifically around this theme. In the midst of AI developments that lead to doubts or even fear, we put some necessary focus on the positive influence AI has and will have on our lives and the real world around us. Please join the discussions and get to know in detail what is happening in the center of Brainport’s AI research.

At EAISI 1000+ AI-researchers do research on AI systems where the physical, digital, and human worlds come together. EAISI aims to get to a better understanding, better designs, better models, and better decisions in the application areas of Health, Mobility, and High-Tech Systems.

Timetable EAISI Research Track

11:00   Coffee break and Expo

11:30   Dominique Fürst -     Moderator

11:35   Alessandro Saccon

12:00  Mauro Salazar

12:25   Valentina Breschi

12:35   Meike Nauta & Nienke Bakx

13:00  Lunch break and Expo

14:15  Opening afternoon track

14:20  Mathias Funk & Jon Pluyter

14:45  Isel Garcia Grau

15:10   Guang Hu

15:18   Giulia de Pasquale

15:25   Barend de Rooij

15:50   Bert de Vries & Albert Podusenko

Image

Dominique Fürst

Boundary Spanner Artificial Intelligence at innovation Space and EAISI at TU/e

Moderator EAISI Research Track

Dominique will moderate the EAISI Research track for the second time.

 
View LinkedIn profile
                                                                                                                                                                                                                             back to top
Image

Alessandro Saccon

Associate Professor at the department of Mechanical Engineering at TU/e.

Can we trust robots to physically touch the open world? The present and the future

The public, industry, and policy makers  expect robots to be able to physical interact with the open world similarly to what we can do. Recent advancements in machine learning, computational and mechatronics hardware, and model-based engineering are bringing this dream closer to reality. Can we trust these machines?
 

View profile on TU/e website
                                                                                                                                                                                                                             back to top

Image

Mauro Salazar

Assistant Professor at the department of Mechanical Engineering at TU/e.

Autonomous Vehicles, Safety Halo, Mobility Systems, Wellbeing

After quite some starts and stops, autonomous vehicles are finally becoming a reality. Recent advances in AI have significantly accelerated their development. Classical architectures comprising perception-planning-control have been increasingly replaced by end-to-end architectures that are empowered by foundational AI models, leading to remarkable performance levels.

Yet a crucial question arises: How do we guarantee safety in such frameworks so that we can trust them?

 
View profile on TU/e website 
                                                                                                                                                                                                                             back to top
Image

Valentina Breschi

Assistant Professor at the department of Electrical Engineering at TU/e.

Pitch: Trustworthy and explainable models: Collaborate or compete?

In this pitch, I will introduce a framework allowing models with different opacities to compete and/or collaborate to accurately and transparently characterize a phenomenon of interest.

 
View profile on TU/e website
                                                                                                                                                                                                                             back to top
Image

Meike Nauta DUO Talk

Assistant Professor at the department of Philosophy of Tilburg University.

Beyond Explainability: Building Trust through Interactive, Interpretable AI

What makes an AI system truly effective? We dive into the technical foundations of explainable and interactive AI, and show how these concepts play out in real-world applications. We explore how cutting-edge research and the latest AI models meet industry reality.

 
View LinkedIn profile
                                                                                                                                                                                                                             back to top
Image

Nienke Bakx DUO Talk

AI Consultant

Beyond Explainability: Building Trust through Interactive, Interpretable AI

What makes an AI system truly effective? We dive into the technical foundations of explainable and interactive AI, and show how these concepts play out in real-world applications. We explore how cutting-edge research and the latest AI models meet industry reality.

 
View LinkedIn profile
                                                                                                                                                                                                                             back to top
Image

Mathias Funk DUO Talk

Associate Professor of the department Industrial Design

AI has trust issues, a therapy session

Unexpected things happen when innovative AI-based solutions meet people on the ground, working in industry, academia and healthcare: busy professionals need reliable tools, but are given “probabilities”. In this talk we dive into the hospital context and what role AI plays in clinical radiology. This talk is not medical advice.

 
View profile on the TU/e website
                                                                                                                                                                                                                             back to top
Image

Jon Pluyter DUO Talk

Senior UX and Clinical Workflow Designer @ Philips, Research Associate at Industrial Design @TU/e

AI has trust issues, a therapy session

Unexpected things happen when innovative AI-based solutions meet people on the ground, working in industry, academia and healthcare: busy professionals need reliable tools, but are given “probabilities”. In this talk we dive into the hospital context and what role AI plays in clinical radiology. This talk is not medical advice.

 
View LinkedIn profile
                                                                                                                                                                                                                             back to top
Image

Isel Garcia Grau

Assistant Professor at the department of Industrial Engineering and Innovation Sciences at TU/e.

SOFI: A Sparseness-Optimized Feature Importance method

The proposed method, termed Sparseness-Optimized Feature Importance (SOFI), entails solving an optimization problem related to the sparseness of feature importance explanations. 

 
View profile on TU/e website
                                                                                                                                                                                                                             back to top
Image

Meike Nauta DUO Talk
Assistant Professor of the department Mathematics and Computer Science at TU/e and senior AI Consultant.

Beyond Explainability: Building Trust through Interactive, Interpretable AI

What makes an AI system truly effective? We dive into the technical foundations of explainable and interactive AI, and show how these concepts play out in real-world applications. We explore how cutting-edge research and the latest AI models meet industry reality.


View LinkedIn profile
                                                 back to top

DUO Talk Nienke Bakx
AI Consultant



Beyond Explainability: Building Trust through Interactive, Interpretable AI

What makes an AI system truly effective? We dive into the technical foundations of explainable and interactive AI, and show how these concepts play out in real-world applications. We explore how cutting-edge research and the latest AI models meet industry reality.


View LinkedIn profile
                                                 back to top

Image
Image

Mathias Funk DUO Talk
Associate Professor of the department Industrial Design


AI has trust issues, a therapy session

Unexpected things happen when innovative AI-based solutions meet people on the ground, working in industry, academia and healthcare: busy professionals need reliable tools that they can trust, not additional uncertainty. This talk features design research in the hospital context and the role of AI in clinical radiology. Not medical advice.


View profile on TU/e website
                                                                                                                      back to top

DUO Talk Jon Pluyter
Senior UX and Clinical Workflow Designer @ Philips, Research Associate at Industrial Design @TU/e

AI has trust issues, a therapy session

Unexpected things happen when innovative AI-based solutions meet people on the ground, working in industry, academia and healthcare: busy professionals need reliable tools that they can trust, not additional uncertainty. This talk features design research in the hospital context and the role of AI in clinical radiology. Not medical advice.

View LinkedIn profile
                                                                                                                        back to top

Image
Image

Guang Hu

Assistant Professor at the department of Mechanical Engineering at TU/e.

Pitch: Trusting AI for Sustainable Energy Integration

How can we design trustworthy AI systems that balance automation with human oversight in complex urban energy networks?" We propose a comprehensive framework for establishing trust in AI-powered energy integration hubs, focusing on transparency in decision-making, validation through real-world testing, and human-AI collaborative approaches. 

 
View profile on TU/e website
                                                                                                                                                                                                                             back to top
Image

Giulia De Pasquale

Assistant Professor at the department of Electrical Engineering at TU/e.

Pitch: Mitigating Biases in Decision-Making Systems

In this pitch I will show how existence of feedback loops in the machine learning-based decision-making pipeline can perpetuate and reinforce machine learning biases and propose strategies to counteract their undesired effects.

 
View profile on TU/e website
                                                                                                                                                                                                                             back to top
Image

Barend de Rooij

Assistant Professor at the department of Philosophy of Tilburg University.

Trust as a Techno-epistemic Virtue

How can we design trustworthy AI systems that balance automation with human oversight in complex urban energy networks?" We propose a comprehensive framework for establishing trust in AI-powered energy integration hubs, focusing on transparency in decision-making, validation through real-world testing, and human-AI collaborative approaches. 

 

View profile on the website of Tilburg University

                                                                                                                                                                                                                             

back to top

Image

Bert de Vries DUO Talk

Full Professor at the department of Electrical Engineering

How to Trust AI: Embracing Uncertainty with Probabilistic Methods

In today's high-stakes business environment, deploying AI systems that stakeholders can genuinely trust isn't optional—it's essential. While organizations rush to adopt AI capabilities, few address the fundamental issue undermining trust: uncertainty. Probabilistic approaches offer a mathematically rigorous solution to this challenge that deterministic methods cannot match.

 
View profile on the TU/e website
                                                                                                                                                                                                                             back to top
Image

Albert Podusenko DUO Talk

University Researcher at the department of Electrical Engineering and the BIAS lab at TU/e and CEO of Lazy Dynamics.

How to Trust AI: Embracing Uncertainty with Probabilistic Methods

In today's high-stakes business environment, deploying AI systems that stakeholders can genuinely trust isn't optional—it's essential. While organizations rush to adopt AI capabilities, few address the fundamental issue undermining trust: uncertainty. Probabilistic approaches offer a mathematically rigorous solution to this challenge that deterministic methods cannot match.

 
View profile on the TU/e website
                                                                                                                                                                                                                             back to top
Image

Bert de Vries DUO Talk
Full Professor at the department of Electrical Engineering


How to Trust AI: Embracing Uncertainty with Probabilistic Methods

In today's high-stakes business environment, deploying AI systems that stakeholders can genuinely trust isn't optional—it's essential. While organizations rush to adopt AI capabilities, few address the fundamental issue undermining trust: uncertainty. Probabilistic approaches offer a mathematically rigorous solution to this challenge that deterministic methods cannot match.

View profile on TU/e website
                                                 back to top

DUO Talk Albert Podusenko
University Researcher at the department of Electrical Engineering and the BIAS lab at TU/e and CEO of Lazy Dynamics.

How to Trust AI: Embracing Uncertainty with Probabilistic Methods

In today's high-stakes business environment, deploying AI systems that stakeholders can genuinely trust isn't optional—it's essential. While organizations rush to adopt AI capabilities, few address the fundamental issue undermining trust: uncertainty. Probabilistic approaches offer a mathematically rigorous solution to this challenge that deterministic methods cannot match.

View profile on TU/e website 
                                                 back to top

Image